Issue 1 (207), article 4


Cybernetics and Computer Engineering, 2022, 1(207)

L.S. Zhiteckii, PhD (Engineering),
Acting Head of the Department of
Intelligent Automatic Systems

International Research and Training Center for
Information Technologies and Systems of the
National Academy of Sciences of Ukraine
and Ministry of Education and Science of Ukraine,
40, Acad. Glushkov av., Kyiv, 03187, Ukraine


Introduction. The improvement of automatic control systems via their intellectualization is the important problem from both theoretical and practical points of view. The presence of adaptation and learning processes intrinsic to the natural intelligence makes it possible to consider the modern adaptive and learning systems as some intelligent control systems of the simplest type.

The purpose of this paper is to outline briefly the world-class results related to the efficient adaptive control and achieved in Intelligent Automatic Systems Department during the last 25 years and also to point out on problems of future research in this scientific area.

Results. A new adaptive control theory which has recently been completed represent the significant achievement to deal with the control systems in the presence of both parameter and nonparameter uncertainties. The main distinguishing feature of this theory is that it requires no information about the constrained membership set of unknown plant parameters and the bounds on arbitrary unmeasurable disturbances. Utilizing its methods, we can ensure the desired performance indices of the control systems with uncertain plants whereas the existing methods become quite unacceptable in the same situation.

Conclusion. Based on recent results concerning the adaptation and learning problems, we propose to take a next step toward to novel intelligent automatic control systems containing complex nonlinear plants. However, new perspective methods guaranteeing a perfect behavior of the closed-loop control systems, in particular, the stability of these control systems should be devised before implementing them in practical applications. This as yet unsolved scientific problem remains the subject of future theoretical research.

Keywords: adaptive and learning control system, automatic intelligent control system, parameter and nonparameter uncertainties, unmeasured disturbance, complex nonlinear plant. 

Download full text!

1. Kuntsevich V.M. Control under uncertainty: guaranteed results in management and identification problems. Kyiv: Nauk. dumka, 2006, 264 p. (in Russian).

2. Goodwin G.C., Sin1. Kuntsevich V.M. Control under uncertainty: guaranteed results in management and identification problems. Kyiv: Nauk. dumka, 2006, 264 p. (in Russian).

2. Goodwin G.C., Sin K.S. Adaptive filtering, prediction and control. Engewood Cliffs, NJ: Pren-tice-Hall, 1984, 540 p.

3. Fomin V.N., Fradkov A.L., Yakubovich V.A. Adaptive control of dynamic plants. Moscow: Nauka, 1981, 448 p (in Russian).

4. Zhiteckij L.S., Skurikhin V.I. Adaptive control systems with parametric and nonparametric uncertainties. Kyiv: Nauk. dumka, 2010, 301 p. (in Russian).

5. Zhiteckij L.S. An open problem in adaptive nonlinear control theory. Unsolved Problems in Mathematical Systems and Control Theory: V.D. Blondel and A. Megretskl (Eds). Princeton, USA: Princeton University Press. 2004. P. 229-237.

6. Zhiteckii L.S., Solovchuk K.Yu. Robust adaptive controls for a class of nonsquare memoryless systems. Advanced Control Systems: Theory and Applications: Kondratenko Y.P., Kuntsevich V.M., Chikrii A.A., Gubarev V.F. (Eds). Gistrup: River Publishers. 2021, pp. 203-226.

7. Gritsenko V.I., Zhiteckii L.S., Solovchuk K.Yu. Limitations of pseudo inverse method for control of linear interconnected memoryless plants: guaranteed results. Dopovidi NAN Ukrainy. 2019, No 8, pp. 16-24 (in Russian).

8. Skurikhin V.I., Gritsenko V.I., Zhiteckii L.S., Solovchuk K. Yu. Generalized inverse operator method in the problem of optimal controlling linear interconnected static plants. Dopovidi NAN Ukrainy. 2014, No 8, pp. 57-66 (in Russian).

9. Zhitetskii L. S., Skurikhin V. I., Solovchuk K.Yu. Stabilization of a nonlinear multivariable discrete-time time-invariant plant with uncertainty on a linear pseudoinverse model. Journal of Computer and Systems Sciences International. 2017, N 5, pp. 12-26.

10. Zhiteckii L. S., Solovchuk K. Yu. Pseudoinversion in the problems of robust stabilizing multivariable discrete-time control systems of linear and nonlinear static objects under bounded disturbances. Journal of Automation and Information Sciences. 2017, N 3, pp. 57-70.

11. Fainzilberg L.S. Intelligent information technology for processing of signals with localized information. Schtuchnyi intelekt. 2008, No 2, pp. 100-110 (in Russian).

12. Timofeev A.V., Yusupov R.M. Intelligent automatic control systems. Technicheskaya kibernetika. 1994, No 5, pp. 211-223 (in Russian).

13. Zhiteckii L. S., Nikolaienko S. A., Solovchuk K. Yu. Adaptation and learning in some classes of identification and control systems. Upravla!û!!ŝ!ie sistemy i ma!š!iny. 2015, No 181, pp. 47-65.

14. Intelligent automatic control systems: I.M. Makarov and R.M. Yusupov (Eds). Moscow: State press for physics and mathematical literature, 1991, 576 p. (in Russian).

15. Gritsenko V.I. Intellectualization of information technologies. Nauka i tehnologiyi. Kyiv: V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine, 1992, pp. 4-9 (in Ukrainian).

16. Skurikhin V.I., Nikulin V.N., Drymalyk Ya.P. Computing devices in contact welding schemes. Voprosy vychislitel’noy tehniki. Kyiv: State press for technical literature of the Ukrainian SSR, 1961, pp. 105-113 (in Russian).

17. Fel’dbaum A.A. Computing devices in automatic systems. Moscow: State press for physics and mathematical literature, 1959, 798 p. (in Russian).

18. Zhuk K.D., Pyatenko T.G., Skurikhin V.I. Problems of synthesis of control models in multiconnected automatic systems. Methods for mathematical modeling and the theory of electrical chain: Proc. of the workshop. Kyiv: Press of the AS of Ukrainian SSR, 1964, pp. 3!−!17 (in Russian).

19. Pukhov G.Ye., Zhuk K.D. Synthesis of multiconnected control systems by the method of inverse operators. Kyiv: Nauk. dumka, 1966, 218 p. (in Russian).

20. Lee T., Adams G., Gaines W. Computer process control: modeling and optimization. NY: Wiley, 1968, 312 p.

21. Lyubchik L.M. Inverse model control and subinvariance in linear discrete multivariable systems. 3rd European Control Conf. Roma, 1995, Vol. 4, part 2, pp. 3651!−!3659.

22. Krut’ko P.D. Inverse problems of control system dynamics: linear models. Moscow: Nauka, 1987, 304 p. (in Russian).

23. Yakubovixh Ye.D. Solving one problem of optimal control for a discrete linear system. Automatika i telemechanika. 1975, No 9, P. 73-79 (in Russian).

24. Vidyasagar M. Optimal rejection of persistent bounded disturbances. IEEE Trans. Autom. Control. 1986, V 31, pp. 527-535.

25. Zhiteckij L.S. On a problem of synthesis of a program control system containing a digital computer. Avtomatyka. 1964, No 5, pp. 36-42 (in Ukrainian).

26. Zhiteckij L.S. Problems of dynamic errors compensation in digital program control systems: PhD Thesis. Kyiv, 1968, 186 p. (in Russian).

27. Astr!ö!m K.J., Hagander P., Sternby J. Zeros of sampled systems. Automatica. 1984, Vol. 20, N 1, pp. 31-38.

28. Zhiteckij L.S. On the invariance of sampled combined program systems. Avtomatyka. 1967, No 6, pp. 83-85 (in Ukrainian).

29. Gross E., Tomizuka M. Experimental flexible beam tip tracking control with a truncated series approximation in uncancelable inverse dynamics. IEEE Trans. on Control Systems Technology. 1994, No 2(4), pp. 382-391.

30. Skurikhin V.I., Zhiteckij L.S., Protsenko N.M. Iterative table automata. Kyiv: Nauk. dumka, 1977, 165 p. (in Russian).

31. Bondarko V.A. Adaptive suboptimal control of solutions of linear difference equations. Doklady AN SSSR. 1983, No 2, pp. 301-303 (in Russian).

32. Zhiteckij L.S. Adaptive control of systems subjected to bounded disturbances. Bounding ap-proaches to system identification: M. Milanese etc. (Eds.). New York, London: Plenum Press, 1996, Chapt. 24, pp. 383-407.

33. Feng G.A robust discrete-time direct adaptive control algorithm. Systems and Control Letters. 1994, V. 22, pp. 203-208.

34. Zhitetskij L. S. Adaptive control under conditions of the presence of disturbances: an identification approach. Problemy Upravleniya i Informatiki. 1996. N 6, P. 66 – 77.

35. Suarez D.A., Lozano R. Adaptive control of nonminimum phase systems subject to unknown bounded disturbances. IEEE Trans. Automat. Control. 1996, No 12, pp. 1830-1836.

36. Zhiteckij L.S. Adaptive control of nonminimum phase systems in the presence of bounded disturbance with unknown bound. Proc. 3rd European Control Conf. (Roma, Italy, 5-8 Sept., 1995), 1995, V 3, pp. 891-896.

37. Zhiteckij L.S. Solution of dissipativity problem for adaptive control system of nonminimum phase plant based on set-membership estimation method. Journal of Automation and Information Sciences. 2001, No 33, pp. 59-69.

38. Zhitetskij L.S. Robustness conditions of adaptive control systems with parametric and nonparametric uncertainties. Journal of Automation and Information Sciences. 1997, No 3, pp. 41-51.

39. Kreisselmeier G., Anderson B.D.O. Robust model reference 8adaptive control. IEEE Trans. utomat. Control. 1986, AC-31, No 2, pp. 127-133.

40. Zhiteckij L.S., Skurikhin V.I., Tyupa O.V, Sapunova N.A. Adaptive discrete-time PID control algorithm for controlling infinite-dimensional systems. Proc. European Control Conference ECC-2001 (Porto, Portugal, September 4-7, 2001), 2001, pp. 184-189.

41. Zhiteckij L.S., Skurikhin V. I., Tyupa O. V Tuning and self-tuning of discrete-time PID controllers based on model reduction approach. Proc. IFAC Workshop on Digital Control: Past, Present and Future of PID Control (Terrassa, Spain, April 5-7, 2000), 2000, pp. 167-172.

42. Zhiteckii L.S. Robust control of some classes of nonlinear discrete-time plants using linear controllers. Journal of Automation and Information Sciences. 2016, No 48, pp. 383-407.

43. Zhiteckij L.S. Singularity-free stable adaptive control of a class of nonlinear discrete-time systems. Proc. 15th IFAC World Congress (Barcelona, Spain, July 21-26, 2002), 2002, pp. 475-480.

44. Skurikhin V.I., Zhitetskij L.S. Control of thermo- and mass exchange processes by using of adjusted models: practical examples. Upravla!û!!ŝ!ie sistemy i ma!š!iny. 2002, No 6, pp. 77-84 (in Russian).

45. Zhiteckii L.S., Azarskov V.N., Nikolaienko S.A., Solovchuk K.Yu. Some features of neural networks as nonlinearly parameterized models of unknown systems using an online learning algorithm. Journal of Applied Mathematics and Physics. Jan. 2018, No 6, pp. 247-263.

Received 21.03.2022